204 research outputs found
An analysis of global warming in the Alpine region based on nonlinear nonstationary time series models
No full textThe annual temperatures recorded for the last two centuries in fifteen european stations around the Alps are analyzed. They show a global warming whose growth rate is not however constant in time. An analysis based on linear Arima models does not provide accurate results. Thus, we propose threshold nonlinear nonstationary models based on several regimes both in time and in levels. Such models fit all series satisfactorily, allow a closer description of the temperature changes evolution, and help to discover the essential differences in the behavior of the different stations
Time-varying multi-regime models fitting by genetic algorithms
No full textMany time series exhibit both nonlinearity and non-stationarity. Though both features have been often taken into account separately, few attempts have been proposed for modelling them simultaneously. We consider threshold models, and present a general model allowing for different regimes both in time and in levels, where regime transitions may happen according to self-exciting, or smoothly varying or piecewise linear threshold modelling. Since fitting such a model involves the choice of a large number of structural parameters, we propose a procedure based on genetic algorithms, evaluating models by means of a generalized identification criterion. The performance of the proposed procedure is illustrated with a simulation study and applications to some real data
Multi-regime models for nonlinear nonstationary time series
No full textNonlinear nonstationary models for time series are considered, where the series is generated from an autoregressive equation whose coefficients change both according to time and the delayed values of the series itself, switching between several regimes. The transition from one regime to the next one may be discontinuous (self-exciting threshold model), smooth (smooth transition model) or continuous linear (piecewise linear threshold model). A genetic algorithm for identifying and estimating such models is proposed, and its behavior is evaluated through a simulation study and application to temperature data and a financial index
Knowledge construction with multiple external representations
No full textSchwonke R, Renkl A, Berthold K. Knowledge construction with multiple external representations. In: Vosniadou S, Kayser D, Protopapas A, eds. Proceedings of EuroCogSci07. Hove: Erlbaum; 2007: 238-243
Nonlinear non stationary model building by genetic algorithms
No full textMany time series exhibits both nonlinearity and nonstationarity. Though both features have been often taken into account separately, few attempts have been proposed for modeling them simultaneously. We consider threshold models and present a general model allowing for several different regimes both in time and in levels, where regime transitions may happen according to self-exciting, or smoothly varying, or piecewise linear threshold modeling. Since fitting such a model involves the choice of a large number of structural parameters, we propose a procedure based on genetic algorithms, evaluating models by means of a generalized identification criterion. The proposed model building strategy is applied to a financial inde
Analysis of speech and silent intervals in naming tasks
No full textProtopapas, Katopodi, Altani, Kolotoura, Sagris, Ziaka, & Georgiou. A process-oriented analysis of speech and silent intervals in responses to serial naming tasks
sj-pdf-3-qjp-10.1177_17470218211047420 – Supplemental material for Lexicality effects on orthographic learning in beginning and advanced readers of Dutch: An eye-tracking study
No full textSupplemental material, sj-pdf-3-qjp-10.1177_17470218211047420 for Lexicality effects on orthographic learning in beginning and advanced readers of Dutch: An eye-tracking study by Sietske van Viersen, Athanassios Protopapas, George K Georgiou, Rauno Parrila, Laoura Ziaka and Peter F de Jong in Quarterly Journal of Experimental Psychology</p
sj-pdf-2-qjp-10.1177_17470218211047420 – Supplemental material for Lexicality effects on orthographic learning in beginning and advanced readers of Dutch: An eye-tracking study
No full textSupplemental material, sj-pdf-2-qjp-10.1177_17470218211047420 for Lexicality effects on orthographic learning in beginning and advanced readers of Dutch: An eye-tracking study by Sietske van Viersen, Athanassios Protopapas, George K Georgiou, Rauno Parrila, Laoura Ziaka and Peter F de Jong in Quarterly Journal of Experimental Psychology</p
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